How human behaviour amplifies the bullwhip effect. A study based on the beer distribution game online

Nienhaus, Jörg; Ziegenbein, Arne; Schoensleben, Paul

doi:10.1080/09537280600866587

Cited by 88 publications

(54 citation statements)

References 4 publications

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“…The bullwhip effect persists in most cases (Croson & Donohue, 2005;Croson & Donohue, 2006;Wu & Katok, 2006;Nienhaus et al, 2006;Croson et al, 2014). Sterman (1989) understood the order volatility from the perspective of bounded rationality and sub-optimal decisions.…”

Section: Experimental Researchmentioning

confidence: 94%

The bullwhip effect: Progress, trends and directions

Wang

Disney

2016

European Journal of Operational Research

318

141

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Section: Experimental Researchmentioning

confidence: 94%

The bullwhip effect: Progress, trends and directions

Wang

Disney

2016

European Journal of Operational Research

318

141

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“…For example, Nienhaus et al (2006) suggest that human capital is one of the important factors to cause the bullwhip effect. In addition, Bhattacharya and Bandyopadhyay(2011) survey the existing literature and summarize 19 important bullwhip effect causes.…”

Section: Discussionmentioning

confidence: 99%

Impacts of Order Cycle Time on the Bullwhip Effect: A Numerical Study

Li¹,

Choi²

2017

JMPP

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The bullwhip effect phenomenon refers to the amplification of demand variability as movingaway from the end customers to the suppliers in a supply chain. This research is concerned with the impacts of order cycle time on the bullwhip effect by considering its four major causes, i.e., demand forecast, price fluctuation, anticipation of shortages, andorder batching. Considering a two-echelon supply chain, fournumerical examples are developed where a multi-period inventory system with a periodic review policy is used.In each order cycle, a replenishment is initiated to raise the inventory to the order-up-to level, and the variance ratio of the manufacturer order to the market demand is calculated. Our results show that order cycle time reduction could counterattack four major causes of the bullwhip effect at the same time.

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“…For instance, in economic systems, delays appear in a natural way since decisions and effects are separated by some time interval. The delay effects on the stability of systems is a problem of recurring interest since the delay presence may induce complex and undesired behaviours (oscillation, instability and bad performance) for the schemes (Shi 1998, Niculescu and Gu 2004, Wang et al 2005, Nienhaus and Ziegenbein 2006, Xia et al 2007, Esfanjani et al 2009, Ignaciuk and Bartoszewicz 2009, Wang and Gao 2009. In this paper, we study stability of logistics networks modelled as a system of delay-differential equations as well.…”

Section: Introductionmentioning

confidence: 97%

Stability analysis of logistics networks with time-delays

Karimi

Kosmykov

2012

Production Planning & Control

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Logistics network represents a complex system where different elements that are logistic locations interact with each other. This interaction contains delays caused by time needed for delivery of the material. In this paper, we study local input-to-state stability of such logistics networks. Their behaviour is described by a functional differential equation with a constant time-delay. An appropriate Lyapunov-Razumikhin function and the small gain condition are utilized to establish some conditions for stability analysis of the network under consideration. Our stability conditions for the logistics network are based on the information about the interconnection properties between logistic locations and their production rates. Finally, numerical results are provided to demonstrate an application of the proposed approach.

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How human behaviour amplifies the bullwhip effect. A study based on the beer distribution game online

Cited by 88 publications

References 4 publications

The bullwhip effect: Progress, trends and directions

The bullwhip effect: Progress, trends and directions

Impacts of Order Cycle Time on the Bullwhip Effect: A Numerical Study

Stability analysis of logistics networks with time-delays

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